With the success of new speech-based human-computer interfaces, there is a great need for effective task-oriented dialogue agents that can handle everyday tasks such as scheduling events and booking hotels. Current commercial dialogue agents are often brittle pattern-matching systems which are unable to maintain the kind of flexible conversations that people desire. Neural dialogue agents present one of the most promising avenues for leveraging dialogue corpora to build statistical models directly from data by using powerful distributed representations  [1]}, [2]}, [3]}.
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